Hillhouse Capital
Liang Wu & colleagues’ contribution of the China section provides an overview of the world’s
largest market of Internet users.

Participants in Evolution of Internet Connectivity
From creators to consumers who keep us on our toes 24x7 + the people who directly help us
prepare the report. And, Kara & team, thanks for continuing to do what you do so well.

2
Context

We use data to tell stories of business-related trends we focus on. We hope others take the ideas, build on
them & make them better.

At 3.6B, the number of Internet users has surpassed half the world’s population. When markets reach
mainstream, new growth gets harder to find - evinced by 0% new smartphone unit shipment growth in
2017.

Internet usage growth is solid while many believe it’s higher than it should be. Reality is the dynamics of
global innovation & competition are driving product improvements, which, in turn, are driving usage &
monetization. Many usability improvements are based on data - collected during the taps / clicks /
movements of mobile device users. This creates a privacy paradox...

Internet Companies continue to make low-priced services better, in part, from user data. Internet Users
continue to increase time spent on Internet services based on perceived value. Regulators want to ensure
user data is not used ‘improperly.’

Scrutiny is rising on all sides - users / businesses / regulators. Technology-driven trends are changing so
rapidly that it’s rare when one side fully understands the other...setting the stage for reactions that can have
unintended consequences. And, not all countries & actors look at the issues through the same lens.

Source: eMarketer 9/14 (2008-2010), eMarketer 4/15 (2011-2013), eMarketer 4/17 (2014-2016), eMarketer 10/17 (2017). Note:
Other connected devices include OTT and game consoles. Mobile includes smartphone and tablet. Usage includes both home and 11
work for consumers 18+. Non deduped defined as time spent with each medium individually, regardless of multitasking.
Internet Usage…

Source: WiGLE.net as of 5/29/18. Note: WiGLE.net is a submission-based catalog of wireless
networks that has collected >6B data points since launch in 2001. Submissions are not paired 16
with actual people, rather name / password identities which people use to associate their data.
Simplicity =
Easy-to-Use Products Becoming Pervasive

Source: Visa Innovations in a Cashless World 2017. Note: Full question was ‘Please think about the payments you make for everyday transactions (excluding rent,
mortgage, or other larger, infrequent payments). Thinking of your past 10 everyday transactions, how many were made in each of the following ways?’, GfK
Research conducted the survey with n = 9,200 across 16 countries (USA, Canada, UK, France, Poland, Germany, Mexico, Brazil, Argentina, Australia, China, India, 18
Japan, South Korea, Russia, UAE), between 7/27/17 – 9/5/17. All respondents do not work in Financial Services, Marketing, Marketing Research, Advertising, or
Public Relations, own and currently use a smartphone, have a savings or checking account; own/use a computer or tablet, and own a credit or debit card.
…Payments =
Friction Declining...

Source: Zenith Online Video Forecasts 2017 (7/17). Note: Based on a study across 63 countries. The
historical figures are taken from the most reliable third-party sources in each market including Nielsen 23
and comScore. The forecasts are provided by local experts, based on the historical trends,
comparisons with the adoption of previous technologies, and their judgement.
…Video =
New Content Types Emerging

Source: Facebook (4/18). Note: Facebook Daily Active Users (DAU) defined as a registered Facebook user who
logged in and visited Facebook on desktop or mobile device, or took action to share content or activity with his or 32
her Facebook friends or connections via a third-party website that is integrated with Facebook, on a given day.
ARPDAU calculated by dividing annualized total revenue by average DAU in the quarter.
...Rising Monetization + Data Collection =
Drives Regulatory Scrutiny

Data / Privacy Competition

The European Data Protection Regulation will be Commission fines Google €2.42 billion for abusing
applicable as of May 25th, 2018 in all member states dominance as search engine by giving illegal
to harmonize data privacy laws across Europe. advantage to its own comparison shopping service.
- European Union, 5/18 - European Commission, 6/17

Source: Square (5/18). Note: Active Sellers have accepted five or more payments using Square in the last 12
months. In 11/15 Square disclosed it had 2MM users and in 3/16 disclosed it was adding 100K sellers per quarter 51
– assuming seller trends remained constant, Square had approximately 2.8MM active sellers at the end of 2017.
(~2.8MM = 2017E)
...Build Online Store…

0% 50% 100%
Bought Online Immediately
Never Bought / Other
% of Respondents that Have Discovered
Products on Platform, USA (18-34 Years Old) % of Respondents, USA (18-65 Years Old)

Source: Curalate Consumer Survey 2017 (8/17). Note: n = 1,000 USA consumers ages 18-65. Left chart
question: ‘In the last 3 months, have you discovered any retail products that you were interested in buying on 71
any of the following social media channels?’ Right chart question: ‘What action did you take after discovering
a product in a brand’s social media post?’ Never Bought / Other includes offline purchases made later.
Social Media =
Share of E-Commerce Referrals Rising @ 6% vs. 2% (2015)

…through technology & consumer insights,
we [Alibaba] put the right products in front of right customers at the right time…
our ‘New Retail’ initiatives are substantially growing Alibaba’s total addressable
market in commerce…
in this process of digitizing the entire retail operation,
we are driving a massive transformation of the traditional retail industry.

It is fair to say that our e-commerce platform is
fast becoming the leading retail infrastructure of China.

Since Jack Ma coined the term ‘New Retail’ in 2016,
the term has been widely adopted in China by
traditional retailers & Internet companies alike.
New Retail has become the most talked about concept in business…

Alibaba has three unique success factors that are
enabling us to realize the New Retail vision.

…Alibaba’s
marketplace platforms handle billions of transactions each month
in shopping, daily services & payments.
These transactions provide us with the
best insights into consumer behavior
& shifting consumption trends. This puts us in the best position to
enable our retail partners to grow their business.
…Alibaba is a deep technology company.
We contribute expertise in cloud, artificial intelligence,
mobile transactions & enterprise systems to help our
retail partners improve their businesses
through digitization & operating efficiency.
…Alibaba has the most
comprehensive ecosystem of commerce platforms, logistics & payments
to support the digital transformation of the retail sector.

Source: Alibaba, Pitchbook. *Percentages represent international commerce revenue proportion of total revenue. Note: All
figures are calendar year. Revenue figures translated using the USD / CNY = 6.76, the average rate for 2017. Grey indicates 94
a majority control stake, all others are minority investments. Country based on headquarters, not countries of operation.
Alibaba International Commerce revenue includes revenue generated from AliExpress, Lazada, and Alibaba.com.
INTERNET ADVERTISING =

Source: USA Census Bureau (6/17). Note: Data reflects newly built housing stock. Single Family homes includes newly built single family homes. Similar
growth trends are seen across all housing units, as single-family homes are the majority of new USA housing stock. Average size of multifamily new 120
dwelling in USA = 1,095 square feet in 1999 (earliest data available), 1,207 square feet in 2016. Residents per household based on all households.
USA Office Space =
Steadily Getting Denser / More Efficient

Source: New York Times, 2/26/1928, article by Evans Clark. Originally sourced from Louis Anslow, “Robots have been about to take all the jobs for more than 200
years,” Timeline, 5/7/16. The New York Times, 2/24/1940, article by Louis Stark. Originally sourced from Louis Anslow, “Robots have been about to take all the jobs 148
for more than 200 years,” Timeline, 5/7/16. The New York Times, 5/4/1962, article by Milton Bracker. New York Times, 9/3/1940, article by Harley Shaiken. Originally
sourced from Louis Anslow, “Robots have been about to take all the jobs for more than 200 years,” Timeline, 5/7/16. 2017 Article = The New York Times.
New Technologies =
Aircraft Jobs Replaced Locomotive Jobs...

New Jobs / Services +
Efficiencies + Growth Typically
Created Around New Technologies

153
Job Market =

Solid Based on Traditional
High-Level Metrics, USA

154
Unemployment @ 3.9% =
Well Below 5.8% Seventy Year Average

Unemployment Rate

30%
Unemployment Rate, USA

20%

10%

Average = 5.8%

0%
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2018

Source: St Louis Federal Reserve FRED Database, Bureau of the Budget (1957). Note: Unemployment rate calculated
by diving the total workforce by the total number of unemployed people. People are classified as unemployed if they do 155
not have a job, have actively looked for work in the prior 4 weeks and are currently available for work.
Consumer Confidence = High & Rising…
Index @ 100 vs. 87 Fifty-Five Year Average

Source: St Louis Federal Reserve FRED Database. *A job opening is defined as a non-farm specific position
of employment to be filled at an establishment. Conditions include the following: there is work available for 157
that position, the job could start within 30 days, and the employer is actively recruiting for the position.
Job Growth =
Stronger in Urban Areas Where 86% of Americans Live

Job / Population Growth – Urban vs. Rural (Indexed to 2001)

120

Jobs = +19%

Population = +15%
110

Jobs = +4%
Population = +4%
100

90
2001 2006 2011 2016

Urban Rural

Source: USDA ERS, BLS. Note: LAUS county-level data from BLS are aggregated into urban (metropolitan/metro) and rural
(nonmetropolitan / non-metro), based on the Office of Management and Budget's 2013 metropolitan classification. Metro areas 158
defined as counties with urban areas >50K in population and the outlying counties where >35% of population commutes to an
urban center for work. ’Rural’ data reflects total non-metro employment, where population has been declining since 2011.
Labor Force Participation @ 63% =
Below 64% Fifty-Year Average...~3.5MM People Below Average*

Labor Force Participation Rate**
90%

80%
Labor Force Participation Rate, USA

70%

60% 64% =
50 Year Average
50%

40%

30%

20%

10%

0%
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Source: St Louis Federal Reserve FRED Database, BLS. *In March 2018, ~161.8MM Americans were in the labor force (62.9% participation). Participation @ 50-year
average of 64.3% would imply a labor force of 165.3MM. The labor force participation rate is defined as the section of working population in the age group of 16+ in the 159
economy currently employed or seeking employment. **For data from 1900-1945 the labor force participation rate includes working population over the age of 10.
Most Common Activities For Many Who Don’t Work* =
Leisure / Household Activities / Education

Males* (Ages 25-54) – Daily Time Use

Not In Labor Force In Labor Force

Watching TV +3 Hours

Other Socializing, Relaxing, Leisure +0.7

Other (Including Sleep) +0.6

Household Activities & Services +0.5

Education +0.3

CaringFor
Caring for Non-Household Members +0.01

Caring for Household Members -0.02

Work -5

0 2 4 6 8 10 12 14
Hours per Day, USA, 6/16

Source: 2014 American Time Use Survey, CEA calculations, BLS. Note: Prime-age males defined as men
between the ages of 25-54. Daily hours may not add up to 24 since some individuals do not report all time spent. 160
Household activities include cleaning, cooking, yardwork & home maintenance not related to caregiving.
Job Expectations =

Source: Gallup 2017 State of the American Workplace Note: *Flexible schedule defined as ability to choose own hours of work. Gallup developed
State of the American Workplace using data collected from more than 195,600 USA employees via the Gallup Panel and Gallup Daily tracking in 2015 162
and 2016, and more than 31 million respondents through Gallup's Q12 Client Database. First launched in 2010, this is the third iteration of the report.
Technology = Makes Freelance Work Easier to Find…
Freelance Workforce = 3x Faster Growth vs. Total Workforce

Has Technology Has Made It Workforce Growth –
Easier To Find Freelance Work? Freelance vs. Total

Uber Source: Uber Note: ~900K USA Uber Driver-Partners. As of 1/15, based on historical growth rates, it is estimated that >90% of USA Uber driver-partners drive for UberX.
DoorDash Source: DoorDash. Note: Lifetime Dashers defined as the total number of people that have dashed on the platform, most of which are still active. Etsy Source: Etsy. Note: In
2017, 65% of Etsy Sellers were USA-based (1.2MM). Upwork Source: Upwork. Airbnb Source: Airbnb, Note: Airbnb disclosed in 2017 that ~660K of their listings were in USA. A 2017
167
CBRE study of ~256K USA Airbnb listings + ~177K Airbnb hosts in Austin, Boston, Chicago, LA, Miami, Nashville, New Orleans, New York City, Oahu, Portland, San Francisco,
Seattle, & Washington D.C. found 83% of hosts are single-listing hosts / non-full-home hosts. This implies >500K USA hosts.
On-Demand Jobs =

57% = Earn Extra Income 91% = Control Own Schedule
21% = Make Up For Financial Hardship 50% = Do Not Want Traditional Job
19% = Earn Income While Job Searching 35% = Have Better Work / Life Balance
Benefits
$34 Average Hourly Income 11 Average Weekly Hours With
Primary On-Demand Platform
$12K Average Annual Income
37 Average Weekly Hours of Work
24% Average Share of Total Income
(All Types / Platforms)

Source: Average Earnings + Foreclosure Avoidance = ‘Introducing The Living Wage Pledge” Airbnb (9/17), Superhost Gender Identity =
‘Women Hosts & Airbnb” (3/17), Employment Status & Earning Usage = ‘2017 Seller Census Survey’ (5/18). Note: A Superhost is an 173
Airbnb host with a 4.8+ rating, 90% response rate, 10+ stays/year, and 0 cancellations. Superhosts are marked as such on Airbnb.com
No [Uber] driver-partner is ever told where or when to work.
This is quite remarkable – an entire global network miraculously
‘level loads’ on its own.
Driver-partners unilaterally decide
when they want to work and where they want to work.
The flip side is also true – they have unlimited
freedom to choose when they do NOT want to work…
The Uber Network…is able to elegantly match
supply & demand without ‘schedules’ & ‘shifts’…
That worker autonomy of both time & place
simply does not exist in other industries.

- Bill Gurley – The Thing I Love Most About Uber – Above the Crowd, 4/18

Source: American Customer Satisfaction Index (ASCI). *Netflix data from 2016, as ASCI score was not tracked in 2017. Instagram / Facebook
average score used as ‘Facebook’ score. Priceline.com used as ‘Booking Holdings’ score. Note: ASCI is a tool first developed by The University 191
of Michigan to measure consumer satisfaction with various companies, brands, and industries. ACSI surveys 250K USA customers annually via
email, responses to weighted questions are used to create a cross-industry score on a scale of 0-100. Top 2017 Score = 87 (Chick-fil-A).
Google Personalization = Queries…
Drive Engagement + Customer Satisfaction

Source: AlphaWise, Morgan Stanley Research. Note: n = 100 USA / E.U. CIOs. Note: Full Question Text =
‘Which three External IT Spending projects will see the largest percentage increase in spending in 2018?’ 201
AI is one of the most important things
humanity is working on.
It is more profound than electricity or fire…

We have learned to harness fire for the benefits of
humanity but we had to overcome its downsides too.

…AI is really important, but we
have to be concerned about it.
- Sundar Pichai, CEO of Google, 2/18

Source: Wikimedia, USA Congress, EU, Japan Government, South Korea Government, Argentina Government.
Note: Argentina proposed a 2017 draft amendment to the Personal Data Protection Act that would strengthen current regulation 209
and align with most GDPR requirements. Japan enacted an amendment to its Act on Protection of Personal Information that
went into effect on 5/30/17. All EU countries grouped due to passage of EU-wide GDPR laws.
...China =
Encouraging Data Collection

Source: USA National Science Foundation analysis of National Bureau of Statistics (China), Government of Japan, UNESCO, OECD, National Center for Education Statistics, IPEDS, & National Center for Science /
Engineering data. Note: Data for the majority of the countries were collected under same OECD, EU, and UIS guidelines & field groupings in the ISCED-F are similar to fields used in China, a major degree producer.
Natural sciences include agricultural sciences; biological sciences; computer sciences; earth, atmospheric, and ocean sciences; & mathematics. EU-Top 8 for doctoral degrees includes UK / Germany / France / Spain /
Italy / Portugal / Romania / Sweden. EU-Top 8 for first university degrees includes UK / Germany / France / Poland / Italy / Spain / Romania / The Netherlands. The # of S&E doctorates awarded rose from about 8K in
2000 to more than 34K in 2014. Despite the growth in the quantity of doctorate recipients, some question the quality of the doctoral programs in China (Cyranoski et al. 2011). The rate of growth in doctoral degrees in
S&E and in all fields has considerably slowed starting in 2010, after an announcement by the Chinese Ministry of Education indicating that China would begin to limit admissions to doctoral programs & focus on quality
227
of graduate education (Mooney 2007). Also in China, first university degrees increased greatly in all fields, with a larger increase in non-S&E than in S&E fields. China experienced an increase of almost 1.2MM degrees
and up more than 400% from 2000 to 2014. China has traditionally awarded a large proportion of its first university degrees in engineering, but the percentage declined from 43% in 2000 to 33% in 2014.
Artificial Intelligence Focus =
China Government Highly Focused on Developing AI

I’m assuming that [USA’s] lead [in Artificial
Intelligence] will continue over the next five years,
& that China will catch up extremely quickly.

In five years we’ll kind of be at the same level, possibly.

It’s hard to see how China would have
passed us in that period, although their rate of
improvement is so impressively good.
- Eric Schmidt, Chairman, US Defense Innovation Advisory Board,
Keynote Address at Artificial Intelligence & Global Security Summit, 11/13/17

*Disclaimer – The information provided in the following slides is for informational and illustrative purposes only. No representation or warranty, express or implied, is given and no responsibility or
liability is accepted by any person with respect to the accuracy, reliability, correctness or completeness of this Information or its contents or any oral or written communication in connection with it.
Hillhouse Capital may hold equity stakes in companies mentioned in this section. A business relationship, arrangement, or contract by or among any of the businesses described herein may not 237
exist at all and should not be implied or assumed from the information provided. The information provided herein by Hillhouse Capital does not constitute an offer to sell or a solicitation of an offer
to buy, and may not be relied upon in connection with the purchase or sale of, any security or interest offered, sponsored, or managed by Hillhouse Capital or its affiliates.
China Macro Trends =

Source: Subscriber data per iQiyi (3/18). Tencent Video and Youku are not standalone
publicly listed companies hence do not provide regular disclosure on paying 249
subscribers. Tencent Video last announced more than 62MM subscribers in 2/18.
China Team-Based Multiplayer Mobile Games =
Lead Game Time Spent in China

Source: Bernstein Research. Note: Hema data points in chart came from stores in Shanghai and
Hangzhou in 11/17. In Q1:18, more than 50% of Hema store orders were placed online for home delivery. 256
Belle =
Re-Imagining Offline Retail Experience with Online Analytics

Source: IMF 2017 Estimates Note: Ranking excludes countries with public debt less than $10B in 2015. Public
debt includes federal, state and local government debt but excludes unfunded pension liabilities from government 284
defined-benefit pension plans and debt from public enterprises and central banks. FX rates as of 3/28/18.
USA Rising
Debt Drivers =

Source for Valuation and Founders Backgrounds: Based on analysis by the Wall Street Journal, CB Insights, Forbes and Business Insider
Note: Due to varying definitions of unicorns, may not align with various unicorn lists. As of April 2018 there are 105 US-based, venture-backed 291
unicorns (including rumored valuations). *UiPath is headquartered in New York, NY but was originally founded in Romania.
APPENDIX

292
Global Industry Classification System (GICS)
(Slides 39 / 41 / 42)
GICS is a four-tiered, hierarchical industry classification system. It consists of 11 sectors, 24 industry groups, 68 industries and 157 sub-industries.
The GICS methodology is widely accepted as an industry analytical framework for investment research, portfolio management and asset allocation.
Companies are classified quantitatively and qualitatively. Each company is assigned a single GICS classification at the sub-industry level according to
its principal business activity. MSCI and S&P Global use revenues as a key factor in determining a firm’s principal business activity. Earnings and
market, however, are also recognized as important and relevant
information for classification purposes.

Global industry coverage is comprehensive and precise. The classification system is comprised of over 50,000 trading securities across 125 countries,
covering approximately 95% of the world’s equity market capitalization.
Company classifications are regularly reviewed and maintained. Specialized teams from two major index providers — MSCI and S&P Global — have
defined review procedures, refined over nearly 15 years.

This presentation has been compiled for informational purposes only and should not be
construed as a solicitation or an offer to buy or sell securities in any entity, or to invest in
any Kleiner Perkins (KP) entity or affiliated fund.
The presentation relies on data + insights from a wide range of sources, including public
+ private companies, market research firms + government agencies. We cite specific
sources where data are public; the presentation is also informed by non-public
information + insights. We disclaim any + all warranties, express or implied, with respect
to the presentation. No presentation content should be construed as professional advice
of any kind (including legal or investment advice).
We publish the Internet Trends report on an annual basis, but on occasion will highlight
new insights. We may post updates, revisions, or clarifications on the KP website.
KP is a venture capital firm that owns significant equity positions in certain of the
companies referenced in this presentation, including those at
http://www.kleinerperkins.com/companies.
Any trademarks or service marks used in this report are the marks of their respective
owners, who are not participating partners or sponsors of the presentation or of KP or its
affiliated funds + such owners do not endorse the presentation or any statements made
herein. All rights in such marks are reserved by their respective owners.